IBF 5070 Module 5 Written Assignment: Break-Even Prices and Scenarios for the Solar Project Example

How Much Room Is There? Break-Even and Scenario Analysis for the Cumberland Solar Project

Student Name

MBA in Finance, Thomas Edison State University

IBF-5070: Financial Modeling

Mentor Name

Month Day, Year

How Much Room Is There? Break-Even and Scenario Analysis for the Cumberland Solar Project

Introduction

Module 4 found that the Cumberland project's NPV of about $3.1 million could be erased by any one of several realistic changes. Sensitivity tests move one input; break-even finds how far it can move before value vanishes; scenarios move several together. Bodmer (2015) describes break-even values as a way to turn uncertainty into specific targets, which suits a project about to enter negotiations. Each technique answers a different question, and together they show management where it has room to negotiate and where it does not, before any probabilities are attached in the next module.

Break-Even Values

Break-even values were found by solving the model for an NPV of zero at 7 percent, changing one input while holding the rest at the base case.

The project has less than 5 percent of room on its two main revenue drivers. The independent engineer's P90 estimate is 7 percent below P50, so a P90 outcome alone would destroy value. Construction cost has the most room, about $7 million on a $94 million budget.

Scenarios

Scenarios combine changes that could plausibly occur together. A downside scenario combines P90 generation, construction costs 10 percent over budget and market prices after the contract 30 percent below the base case. An upside scenario combines generation 5 percent above P50, construction costs 5 percent under budget and market prices 20 percent above the base case.

The downside loss is larger than the upside gain from the base case, about $15.4 million against $10.2 million. This asymmetry arises because the downside scenario's changes are larger, reflecting the view that cost overruns and weak output are more likely to be severe than their favorable counterparts. Graham and Harvey (2001) found that more than half of the chief financial officers they surveyed used sensitivity or scenario analysis when evaluating projects, which reflects how seldom a single estimate is trusted.

Examining the Output

The scenarios do not say how likely each outcome is; that question is for Module 6. What they do show is that the project's value depends heavily on factors Bayshore can partly control. Two actions follow. First, Bayshore should seek a contract price of at least $72 per MWh, which would raise base-case NPV by about $1.9 million, to about $5.0 million, and widen the room for error on price to about 7 percent. Second, it should sign a fixed-price construction contract at or below $1.20 per watt, removing most of the construction risk in the downside scenario.

Limitations

Break-even analysis holds every other input at its base value, which can be misleading when inputs are related. Scenarios capture relationships, but their choice is a judgment, and a downside that is not severe enough gives false comfort. Hertz (1964) argued that single-point estimates and a few scenarios hide the full range of outcomes, the case for the probabilistic analysis in the next module.

Conclusion

The Cumberland project breaks even at a contract price of $66.72 per MWh, generation 3.7 percent below P50 or construction at $1.28 per watt. A combined downside would cost about $12 million of value. Management should negotiate a contract price of at least $72 and a fixed-price construction agreement before committing.

References

Bodmer, E. (2015). Corporate and project finance modeling: Theory and practice. Wiley.

Graham, J. R., & Harvey, C. R. (2001). The theory and practice of corporate finance: Evidence from the field. Journal of Financial Economics, 60(2-3), 187-243. https://doi.org/10.1016/S0304-405X(01)00044-7

Hertz, D. B. (1964). Risk analysis in capital investment. Harvard Business Review, 42(1), 95-106.